Observations of changes in acoustic emission parameters for varying corrosion defect in reciprocating compressor valves

Abstract Acoustic Emission (AE) technology is probably one of the most recent entries in the field of machinery condition monitoring. This paper investigates the application of AE parameters for valve faults detection in reciprocating compressor. The defective valves were designed by emulating the actual valve corrosion with varying sizes such that defects could be applied onto the reciprocating compressor. A set of experiments was performed to acquire the AE signal. The primary source of AE signal was verified using waveform analysis. The AE parameters versus different operational and valve condition were illustrated individually. In addition, the significance of the change and sensitivity of AE parameters versus different experimental conditions was verified using MANOVA and coefficient of variance analysis. It is concluded that the AE signal parameters can be used to detect the valve faults in the reciprocating compressor with the consideration of the variation in the AE parameters sensitivity.

[1]  M. Jaafar,et al.  The Effect of Velocity in High Swirling Flow in Unconfined Burner , 2014 .

[2]  C. Mukhopadhyay,et al.  On-Line Monitoring of Engineering Components Using Acoustic Emission Technique , 2014 .

[3]  John Alexander Steel,et al.  Monitoring of a large reciprocating compressor. , 1998 .

[4]  L. D Hall.  The transmission of acoustic emission across large-scale turbine rotors , 2002 .

[5]  Yih-Hwang Lin,et al.  Automated valve condition classification of a reciprocating compressor with seeded faults: experimentation and validation of classification strategy , 2009 .

[6]  M. Salman Leong,et al.  Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis , 2016 .

[7]  S. Al-Dossary,et al.  Observations of changes in acoustic emission waveform for varying seeded defect sizes in a rolling element bearing , 2009 .

[8]  D Owen,et al.  Experimental investigation into the capabilities of acoustic emission for the detection of shaft-to-seal rubbing in large power generation turbines: A case study , 2006 .

[9]  Andrew Ball,et al.  Numerical simulation and experimental study of a two-stage reciprocating compressor for condition monitoring , 2008 .

[10]  Haifeng Li,et al.  Fault Diagnosis for Reciprocating Air Compressor Valve Using P-V Indicator Diagram and SVM , 2010, 2010 Third International Symposium on Information Science and Engineering.

[11]  John Alexander Steel,et al.  Recent developments in monitoring of engines using acoustic emission , 2005 .

[12]  David,et al.  A comparative experimental study on the use of acoustic emission and vibration analysis for bearing defect identification and estimation of defect size , 2006 .

[13]  Andrew Ball,et al.  Fault Detection of Reciprocating Compressors using a Model from Principles Component Analysis of Vibrations , 2012 .

[14]  Raja Ishak Raja Hamzah,et al.  Acoustic Emission Signal Analysis and Artificial Intelligence Techniques in Machine Condition Monitoring and Fault Diagnosis: A Review , 2014 .

[15]  Andrew D. Ball,et al.  An approach to fault diagnosis of reciprocating compressor valves using Teager-Kaiser energy operator and deep belief networks , 2014, Expert Syst. Appl..

[16]  Fengshou Gu,et al.  Diesel Engine Valve Clearance Detection Using Acoustic Emission , 2010 .

[17]  Royce N. Brown,et al.  Compressors: Selection and Sizing , 1986 .

[18]  D. Mba,et al.  Acoustic Emission Waveform Changes for Varying Seeded Defect Sizes , 2006 .

[19]  Laibin Zhang,et al.  Research on fault diagnosis for reciprocating compressor valve using information entropy and SVM method , 2009 .

[20]  Bo-Suk Yang,et al.  Condition classification of small reciprocating compressor for refrigeration using artificial neural networks and support vector machines , 2005 .

[21]  M. Salman Leong,et al.  A Review of Acoustic Emission Technique for Machinery Condition Monitoring: Defects Detection & Diagnostic , 2012 .

[22]  Yuefei Wang,et al.  Fault diagnosis of reciprocating compressor valve with the method integrating acoustic emission signal and simulated valve motion , 2015 .

[23]  Sotirios J. Vahaviolos,et al.  Acoustic emission : standards and technology update , 1999 .

[24]  P. KaewTrakulPong,et al.  Investigation of the relationship between internal fluid leakage through a valve and the acoustic emission generated from the leakage , 2010 .

[25]  Masayasu Ohtsu,et al.  Acoustic Emission Testing , 2006, Advanced Materials Research.

[26]  John Alexander Steel,et al.  THE DEVELOPMENT OF AUTOMATED PATTERN RECOGNITION AND STATISTICAL FEATURE ISOLATION TECHNIQUES FOR THE DIAGNOSIS OF RECIPROCATING MACHINERY FAULTS USING ACOUSTIC EMISSION , 2003 .